Identification of endoplasmic reticulum stress genes in human stroke based on bioinformatics and machine learning.

After ischemic stroke (IS), secondary injury is intimately linked to endoplasmic reticulum (ER) stress and body-brain crosstalk. Nonetheless, the underlying mechanism systemic immune disorder mediated ER stress in human IS remains unknown. In this study, 32 candidate ER stress-related genes (ERSRGs) were identified by overlapping MSigDB ER stress pathway genes and DEGs. Three Key ERSRGs (ATF6, DDIT3 and ERP29) were identified using LASSO, random forest, and SVM-RFE. IS patients with different ERSRGs profile were clustered into two groups using consensus clustering and the difference between 2 group was further explored by GSVA. Through immune cell infiltration deconvolution analysis, and middle cerebral artery occlusion (MCAO) mouse scRNA analysis, we found that the expression of 3 key ERSRGs were closely related with peripheral macrophage cell ER stress in IS and this was further confirmed by RT-qPCR experiment. These ERS genes might be helpful to further accurately regulate the central nervous system and systemic immune response through ER stress and have potential application value in clinical practice in IS.

Construction of a ferroptosis and hypoxia-related gene signature in cervical cancer to assess tumour immune microenvironment and predict prognosis.

BACKGROUND: This study aimed to investigate the potential role of ferroptosis/hypoxia-related genes in cervical cancer to improve early management and treatment of cervical cancer. METHODS: All data were downloaded from public databases. Ferroptosis/hypoxia-related genes associated with cervical cancer prognosis were selected to construct a risk score model. The relationship between risk score and clinical features, immune microenvironment and prognosis were analysed. RESULTS: Risk score model was constructed based on eight signature genes. Drug prediction analysis showed that bevacizumab and cisplatin were related to vascular endothelial growth factor A. Risk score, as an independent prognostic factor of cervical cancer, had a good survival prediction effect. The two groups differed significantly in degree of immune cell infiltration, gene expression, tumour mutation burden and somatic variation. CONCLUSIONS: We developed a novel prognostic gene signature combining ferroptosis/hypoxia-related genes, which provides new ideas for individual treatment of cervical cancer.

Ferroptosis, hypoxia and immune regulation play important roles in cervical cancer progression. In this study, we developed a novel prognostic signature combining ferroptosis and hypoxia-related genes, which provides new ideas for individual treatment of cervical cancer patients. The risk score established by ferroptosis and hypoxia-related gene as an independent prognostic factor of cervical cancer has a good survival prediction effect. High and low risk groups showed significant differences in TIME, prognosis, biological metabolic pathway and tumour mutation burden. In addition, we found drugs associated with signature genes. In short, this study has laid a theoretical foundation for exploring the related molecular mechanisms and prognosis of cervical cancer. It also contributes to the exploration of clinical management and treatment.

EGFR ligands synergistically increase IL-17A-induced expression of psoriasis signature genes in human keratinocytes via IκBζ and Bcl3.

Various epidermal growth factor receptor (EGFR) ligands are highly expressed in the epidermis of psoriasis lesions, and abnormal EGFR activation appears to be involved in the pathogenesis of psoriasis. However, how EGFR signaling contributes to the development of psoriasis is unclear. Interleukin (IL)-17A, a critical effector of the IL-23/IL-17A pathway, increases the expression of psoriasis signature genes in keratinocytes and plays an essential role in the pathogenesis of psoriasis by inducing IκBζ, a critical transcriptional regulator in psoriasis. In this study, we stimulated primary human keratinocytes with IL-17A and various EGFR ligands to investigate whether EGFR ligands regulate the expression of psoriasis signature genes. In cultured normal human keratinocytes and a living skin equivalent, EGFR ligands did not induce psoriasis-related gene expression, but significantly enhanced the IL-17A-mediated induction of various psoriasis signature genes, including antimicrobial peptides, cytokines, and chemokines. This was dependent on an EGFR activation-mediated synergistic increase in IL-17A-induced IκBζ expression and was partially mediated by the EGFR-dependent upregulation of Bcl3. Therefore, EGFR ligands can act as synergistic agents of IL-17A signaling by stimulating the epidermal production of psoriasis signature genes in psoriasis lesions. This study reveals a potential mechanism by which EGFR signaling contributes to the pathogenesis of psoriasis.

Functional evaluation of rare OASL variants by analysis of SLE patient-derived iPSCs.

BACKGROUND: Systemic lupus erythematosus (SLE) is a chronic systemic autoimmune disease characterized by genetic heterogeneity and an interferon (IFN) signature. The overall landscapes of the heritability of SLE remains unclear. OBJECTIVES: To identify and elucidate the biological functions of rare variants underlying SLE, we conducted analyses of patient-derived induced pluripotent stem cells (iPSCs) in combination with genetic analysis. METHODS: Two familial SLE patient- and two healthy donor (HD)-derived iPSCs were established. Type 1 IFN-secreting dendritic cells (DCs) were differentiated from iPSCs. Genetic analyses of SLE-iPSCs, and 117 SLE patients and 107 HDs in the ImmuNexUT database were performed independently. Genome editing of the variants on iPSCs was performed with the CRISPR/Cas9 system. RESULTS: Type 1 IFN secretion was significantly increased in DCs differentiated from SLE-iPSCs compared to HD-iPSCs. Genetic analyses revealed a rare variant in the 2'-5'-Oligoadenylate Synthetase Like (OASL) shared between SLE-iPSCs and another independent SLE patient, and significant accumulation of OASL variants among SLE patients (HD 0.93%, SLE 6.84%, OR 8.387) in the database. Genome editing of mutated OASL 202Q to wild-type 202 R or wild-type OASL 202 R to mutated 202Q resulted in reduced or enhanced Type 1 IFN secretion of DCs. Three other OASL variants (R60W, T261S and A447V) accumulated in SLE patients had also capacities to enhance Type 1 IFN secretion in response to dsRNA. CONCLUSIONS: We established a patient-derived iPSC-based strategy to investigate the linkage of genotype and phenotype in autoimmune diseases. Detailed case-based investigations using patient-derived iPSCs provide information to unveil the heritability of the pathogenesis of autoimmune diseases.

Transforming growth factor beta induced (TGFBI) is a potential signature gene for mesenchymal subtype high-grade glioma.

Previous study revealed that higher expression of transforming growth factor beta induced (TGFBI) is correlated to poorer cancer-specific survival and higher proportion of tumor necrosis and Fuhrman grades III and IV in clear cell renal cell carcinomas. However, the relationships between TGFBI expression and malignant phenotypes of gliomas remain unclear. We downloaded and analyzed data from seven GEO datasets (GSE68848, GSE4290, GSE13041, GSE4271, GSE83300, GSE34824 and GSE84010), the TCGA database and the REMBRANDT database to investigate whether TGFBI could be a biomarker of glioma. From microarray data (GSE68848, GSE4290) and RNA-seq data (TCGA), TGFBI expression levels were observed to correlate positively with pathological grade, and TGFBI expression levels were significantly higher in gliomas than in normal brain tissues. Furthermore, in GSE13041, GSE4271 and the TCGA cohort, TGFBI expression in the mesenchymal (Mes) subtype high-grade glioma (HGG) was significantly higher than that in the proneural subtype. Kaplan-Meier survival analysis of GBM patients in the GSE83300 dataset, REMBRANDT and TCGA cohort revealed that patients in the top 50% TGFBI expression group survived for markedly shorter periods than those in the bottom 50%. Analysis of grade III gliomas showed that the median survival time was significantly shorter in the TGFBI high expression group than in the TGFBI low expression group. In addition, we found that TGFBI expression levels might relate to several classical molecular characterizations of glioma, such as, IDH mutation, TP53 mutation, EGFR amplification, etc. These results suggest that TGFBI expression positively correlates with glioma pathological grades and that TGFBI is a potential signature gene for Mes subtype HGG and a potential prognostic molecule.

TYROBP serve as potential immune-related signature genes in the acute phase of intracerebral hemorrhage.

The development of intracerebral hemorrhage (ICH) is a dynamic process and intervention during the acute phase of ICH is critical for subsequent recovery. Therefore, it is crucial to screen potential signature genes and therapeutic target genes in the acute phase of ICH. In this study, based on the results of mRNA sequencing in mouse ICH and mRNA sequencing of human ICH from online databases, top five potential signature genes after ICH, Tyrobp, Itgb2, Tlr2, Ptprc and Itgam, were screened. Quantitative PCR results showed higher mRNA expression of Tyrobp, Itgb2, Tlr2, Ptprc, and Itgam in the 1-, 3- and 5-day mouse ICH groups compared to the sham-operated group. Immune infiltration correlation analysis shows that the top-ranked signature gene, Tyrobp, is negatively correlated with M2 macrophages and plasma cells, and Western blot analysis shows higher expression of the Tyrobp protein in the 1-, 3-, and 5-day mouse ICH groups compared to the sham-operated group. Furthermore, immunohistochemistry revealed that TYROBP protein expression was significantly higher in human ICH tissues than in normal brain tissues. Our results suggest that Tyrobp is a signature gene in the acute phase of ICH and may be a potential target for the treatment of the acute phase of ICH.

Analysis and identification of ferroptosis-related diagnostic markers in rheumatoid arthritis.

BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune, inflammatory joint disease. There is growing evidence that ferroptosis is involved in the pathogenesis of RA. This study aimed to search for diagnostic markers of ferroptosis in RA and to analyse the potential mechanisms and clinical value. MATERIALS AND METHODS: RA-associated datasets were used from the publicly available GEO database. Three methods of machine learning were applied to screen biomarkers. The diagnostic efficacy of the results was also verified by receiver operating characteristic (ROC) curve, external dataset, qRT-PCR and Western blot. Enrichment analysis was performed in this process, while protein-protein interaction (PPI) analysis and immune infiltration correlation analysis were performed using biomarkers, and competing endogenous RNA (ceRNA) networks were constructed to search for prospective therapeutic targets. RESULTS: MMP13 and GABARAPL1 can be used as ferroptosis diagnostic genes in RA. The ROC curve and PPI result demonstrated that MMP13 and GABARAPL1 had an excellent diagnostic value. The results of signature genes in the external dataset, qRT-PCR and Western blot further confirm our findings. The enrichment analysis showed that p53, MAPK and NOD-like receptor signalling pathways may be involved in the process of ferroptosis in RA. In addition, two ferroptosis diagnostic genes in RA participate in the occurrence of ferroptosis in RA via oxidative stress, metabolism and immune response. Immune infiltration analysis showed that RA extensively infiltrated B cells, T cells, macrophages and other immune cells. Persistent immune activation may be an essential reason for the progression of ferroptosis in RA. We also obtained five potential therapeutic agents for RA and some long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) regulating ferroptosis diagnostic genes. CONCLUSIONS: Our study suggests that MMP13 and GABARAPL1, which are closely linked with oxidative stress and immunological modulation, can be used as ferroptosis-related potential diagnostic markers in RA and provide new clues regarding the diagnostic and therapeutic targets of ferroptosis in RA.

Identification of signature gene set as highly accurate determination of metabolic dysfunction-associated steatotic liver disease progression.

BACKGROUND/AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression. METHODS: Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD. RESULTS: After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort. CONCLUSION: We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.

Identification of mitophagy-related genes with potential clinical utility in myocardial infarction at transcriptional level.

Background: Myocardial infarction (MI) ranks among the most prevalent cardiovascular diseases. Insufficient blood flow to the coronary arteries always leads to ischemic necrosis of the cardiac muscle. However, the mechanism of myocardial injury after MI remains unclear. This article aims to explore the potential common genes between mitophagy and MI and to construct a suitable prediction model. Methods: Two Gene Expression Omnibus (GEO) datasets (GSE62646 and GSE59867) were used to screen the differential expression genes in peripheral blood. SVM, RF, and LASSO algorithm were employed to find MI and mitophagy-related genes. Moreover, DT, KNN, RF, SVM and LR were conducted to build the binary models, and screened the best model to further external validation (GSE61144) and internal validation (10-fold cross validation and Bootstrap), respectively. The performance of various machine learning models was compared. In addition, immune cell infiltration correlation analysis was conducted with MCP-Counter and CIBERSORT. Results: We finally identified ATG5, TOMM20, MFN2 transcriptionally differed between MI and stable coronary artery diseases. Both internal and external validation supported that these three genes could accurately predict MI withAUC = 0.914 and 0.930 by logistic regression, respectively. Additionally, functional analysis suggested that monocytes and neutrophils might be involved in mitochondrial autophagy after myocardial infarction. Conclusion: The data showed that the transcritional levels of ATG5, TOMM20 and MFN2 in patients with MI were significantly different from the control group, which might be helpful to further accurately diagnose diseases and have potential application value in clinical practice.

Immune infiltration and immunophenotyping in atrial fibrillation.

Atrial fibrillation (AF) is a relatively common arrhythmia in clinical practice. Although significant progress has been achieved in the treatment of AF and its associated complications, research on AF prevention lags behind, mainly due to the lack of a deep understanding of AF pathogenesis. In recent years, as our knowledge has grown, the role of the inflammatory/immune response in the occurrence and progression of AF has gradually gained attention. In this paper, based on existing gene expression data in the Gene Expression Omnibus database, a detailed description of immune infiltration status in AF is presented using a series of analytical methods, including differential analysis, Gene Ontology categorization, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and weighted gene coexpression network analysis, and analysis tools such as CIBERSORTx and Cytoscape. Several new AF/immune infiltrations-related signature genes were identified, and the AF/immune infiltration pathology was classified based on these immune signature genes, thus providing novel insights into the pathogenesis of AF based on the inflammatory response.